Let’s be honest. Most “AI projects” start as a Jupyter notebook named Untitled12_final_final_v2.ipynb. It lives on a laptop that hasn’t been rebooted in three weeks, runs on a specific version of Python that no longer exists in the wild, and…

As an Architect, your job isn’t to build cool models; it’s to solve business problems with the least amount of technical debt. When you look at Google Cloud’s AI stack, you aren’t looking at a single product. You are looking…

The “Notebook” Obsession Before we talk about Google Cloud’s specific tools, you have to understand the tool every data scientist lives in: the Jupyter Notebook. If you come from a traditional DevOps or software engineering background, notebooks look like insanity.…

Let me start with a scene I’ve lived through too many times. A data scientist walks into the office with that excited “I trained a new model last night” energy. They open a notebook, run a few cells, show a…

If you tried to build an “intelligent” application ten or fifteen years ago something that could look at images, parse text, or transcribe audio you were basically signing up for a science project. You’d need GPUs, a cluster of compute…

As an infrastructure or cloud engineer, your job isn’t just to build; it’s to protect. When you deploy applications to the cloud, you’re exposing them to the public internet, a space filled with threats ranging from automated bots to large-scale…

As an infrastructure engineer, your life revolves around managing state and compute. You build VPCs, you provision GKE clusters, you manage IAM policies, and you provision Dataproc clusters for the data science team. Your world is code, YAML, and gcloud commands. Then, a data analyst…

As an infrastructure or cloud engineer, your world is likely dominated by VMs, VPCs, IAM policies, and GKE clusters. But sooner or later, you’ll be pulled into a conversation that starts with, “We have… a lot of data.” Suddenly, terms like Hadoop,…